• 제목/요약/키워드: Energy estimation

검색결과 2,206건 처리시간 0.03초

Probabilistic Estimation of LMR Fuel Cladding Performance Under Transient Conditions

  • Kwon, Hyoung-Mun;Lee, Dong-Uk;Lee, Byung-Oon;Kim, Young ll;Kim, Yong-Soo
    • Nuclear Engineering and Technology
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    • 제35권2호
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    • pp.144-153
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    • 2003
  • The object of this paper is the probabilistic failure analysis on the cladding performance of WPF(Whole Pin Furnace) test fuel pins under transient conditions, and analysis of the KALIMER fuel pin using the preceding analysis. The cumulative damage estimation and Weibull probability estimation of WPF test are performed. The probabilistic method was adapted for these analyses to determine the effective thickness thinning due to eutectic penetration depth. In the results, it is difficult to assume that a brittle layer depth made by eutectic reaction is all of the thickness reduction due to cladding thinning. About 93% cladding thinning of the eutectic penetration depth is favorable as an effective thickness of cladding. And the unreliability of the KALIMER driver fuel pin under the same WPF test condition is lower than that of the WPF pin because of the higher plenum-fuel volume ratio and lower cladding inner radius vs. thickness ratio. KALIMER fuel pin developed from conceptual design has a more stable transient performance for a failure mechanism due to fission gas buildup than the WPF pin.

Analysis of residential natural gas consumption distribution function in Korea - a mixture model

  • Kim, Ho-Young;Lim, Seul-Ye;Yoo, Seung-Hoon
    • 에너지공학
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    • 제23권3호
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    • pp.36-41
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    • 2014
  • The world's overall need for natural gas (NG) has been growing up fast, especially in the residential sector. The better the estimation of residential NG consumption (RNGC) distribution, the better decision-making for a residential NG policy such as pricing, demand estimation, management options and so on. Approximating the distribution of RNGC is complicated by zero observations in the sample. To deal with the zero observations by allowing a point mass at zero, a mixture model of RNGC distributions is proposed and applied. The RNGC distribution is specified as a mixture of two distributions, one with a point mass at zero and the other with full support on the positive half of the real line. The model is empirically verified for household RNGC survey data collected in Korea. The mixture model can easily capture the common bimodality feature of the RNGC distribution. In addition, when covariates were added to the model, it was found that the probability that a household has non-expenditure significantly varies with some variables. Finally, the goodness-of-fit test suggests that the data are well represented by the mixture model.

건물에너지 분석 방법론 비교 - Steady-state simulation에서부터 Data-driven 방법론의 비교 분석 - (Comparing Methodology of Building Energy Analysis - Comparative Analysis from steady-state simulation to data-driven Analysis -)

  • 조수연;이승복
    • KIEAE Journal
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    • 제17권5호
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    • pp.77-86
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    • 2017
  • Purpose: Because of the growing concern over fossil fuel use and increasing demand for greenhouse gas emission reduction since the 1990s, the building energy analysis field has produced various types of methods, which are being applied more often and broadly than ever. A lot of research products have been actively proposed in the area of the building energy simulation for over 50 years around the world. However, in the last 20 years, there have been only a few research cases where the trend of building energy analysis is examined, estimated or compared. This research aims to investigate a trend of the building energy analysis by focusing on methodology and characteristics of each method. Method: The research papers addressing the building energy analysis are classified into two types of method: engineering analysis and algorithm estimation. Especially, EPG(Energy Performance Gap), which is the limit both for the existing engineering method and the single algorithm-based estimation method, results from comparing data of two different levels- in other words, real time data and simulation data. Result: When one or more ensemble algorithms are used, more accurate estimations of energy consumption and performance are produced, and thereby improving the problem of energy performance gap.

Performance Analysis of Energy-Efficient Secure Transmission for Wireless Powered Cooperative Networks with Imperfect CSI

  • Yajun Zhang;Jun Wu;Bing Wang;Hongkai Wang;Xiaohui Shang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권9호
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    • pp.2399-2418
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    • 2023
  • The paper focuses on investigating secure transmission in wireless powered communication networks (WPCN) that involve multiple energy-constrained relays and one energy-constrained source. The energy is harvested from a power beacon (PB) while operating in the presence of a passive eavesdropper. The study primarily aims to achieve energy-efficient secure communications by examining the impact of channel estimation on the secrecy performance of WPCN under both perfect and imperfect CSI scenarios. To obtain practical insights on improving security and energy efficiency, we propose closed-form expressions for secrecy outage probability (SOP) under the linear energy harvesting (LEH) model of WPCN. Furthermore, we suggest a search method to optimize the secure energy efficiency (SEE) with limited power from PB. The research emphasizes the significance of channel estimation in maintaining the desired performance levels in WPCN in real-world applications. The theoretical results are validated through simulations to ensure their accuracy and reliability.

운용상태를 고려한 집단에너지설비의 최적용량 산정 알고리즘의 개발에 관한 연구 (A Study on the Development of the Optimal Capacity Estimation Algorithm of Intergrated Energy Facilities Based on Operating Conditions)

  • 김창식;송명호;염지훈;신정열
    • 에너지공학
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    • 제28권4호
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    • pp.94-102
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    • 2019
  • 본 연구는 집단에너지 사업자들의 최대 열수요가 발생할 때의 열원설비 운영현황을 분석하여, 이를 수익 최대화 관점에서 현재 설치되어 있는 설비의 운영 최적화 방안을 도출하여 제시하고, 도출된 결과를 토대로 해당 열부하에 대한 CHP(Combined Heat and Power), PLB(Peak Load Boiler) 등의 최적 설비용량 구성방안을 제시함으로서 사업자들이 운용상태까지 고려해서 보다 경제적으로 설비투자를 할 수 있는 가이드라인을 제공하고자 하였다.

공동주택의 건물외부조건과 에너지비용과의 관계분석 (Relation between the Building Exterior Conditions and Energy Costs in the Running period of the Apartment Housing)

  • 이강희;류승훈;이은택
    • KIEAE Journal
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    • 제9권1호
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    • pp.107-113
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    • 2009
  • The energy cost is resulted from the energy use. Its sources are divided into some types and depended on the building use or energy-use type. The energy cost should be affected by the amount of the energy use. The cost could be calculated to consider various factors such as the insulation, heating type, building shape and others. But it can not consider all of the affect factors to the energy cost and need to categorize the factors to the condition for estimating the cost. In this paper, it aimed at providing the estimation model in linear equation and multiple linear regression, utilizing the building exterior condition and management characteristics in apartment housing. Its survey are conducted in two parts of management characteristics and building exterior condition. The correlation analysis is conducted to get rid of the multicolinearity among the inputted factors. The number of linear equation model is 11 and includes the 1st, 2nd and 3rd equation function, power function and others. Among these, it suggested the 2nd and 3rd function and power function in terms of the statistics. In multiple linear regression model, the building volume and management area are inputted to the estimation.

Time-Series Estimation based AI Algorithm for Energy Management in a Virtual Power Plant System

  • Yeonwoo LEE
    • 한국인공지능학회지
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    • 제12권1호
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    • pp.17-24
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    • 2024
  • This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.